Finding semantic structures in image hierarchies using Laplacian graph energy

Authors:
Yi-Zhe Song;Pablo Arbelaez;Peter Hall;Chuan Li;Anupriya Balikai
Affiliations:
MTRC, University of Bath, Bath, UK;University of California at Berkeley, Berkeley, CA;MTRC, University of Bath, Bath, UK;MTRC, University of Bath, Bath, UK;MTRC, University of Bath, Bath, UK
Venue:
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Year:
2010

Citing 14
Cited 3

A Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Color Image Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Region-Based Object Recognition Using Shape-from-Shading

ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Recognizing Objects Using Color-Annotated Adjacency Graphs

Shape, Contour and Grouping in Computer Vision
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues

IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral Segmentation with Multiscale Graph Decomposition

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Mixing spectral representations of graphs

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
A Riemannian approach to graph embedding

Pattern Recognition
Multi-scale Improves Boundary Detection in Natural Images

ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Polytopal Graph Complexity, Matrix Permanents, and Embedding

SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Iterative optimization and simplification of hierarchical clusterings

Journal of Artificial Intelligence Research
An iterative image registration technique with an application to stereo vision

IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2

Robust visual tracking using structural region hierarchy and graph matching

Neurocomputing
Simple object recognition based on spatial relations and visual features represented using irregular pyramids

Multimedia Tools and Applications
Simple art as abstractions of photographs

Proceedings of the Symposium on Computational Aesthetics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Many segmentation algorithms describe images in terms of a hierarchy of regions. Although such hierarchies can produce state of the art segmentations and have many applications, they often contain more data than is required for an efficient description. This paper shows Laplacian graph energy is a generic measure that can be used to identify semantic structures within hierarchies, independently of the algorithm that produces them. Quantitative experimental validation using hierarchies from two state of art algorithms show we can reduce the number of levels and regions in a hierarchy by an order of magnitude with little or no loss in performance when compared against human produced ground truth. We provide a tracking application that illustrates the value of reduced hierarchies.